A blended learning model with IoT-based technology: effectively used when the COVID-19 pandemic?

Abstract

This qualitative research has the purpose to analyze and synthesize a model of Blended Learning (BL) with IoT-based technology. Data sources are related literature, textbooks, research, articles, and websites. The author used analysis and synthesis tables with the content analysis method. IoT-based technology was considered to refer to all heterogeneous objects and devices through any networks, and BL is the educational approach to combine F2F instruction with ICT instruction. Many devices and “things” in IoT-based technology were added in class to create and improve a smart learning environment for the learning goals. This study divided BL into 4 characteristics; F2F, Self-paced, Tele-D, and Ubiquitous, which were further categorized into 3 typical cases of learning environments, Digital, Embedded, and Side-by-side cases. A framework of this model has 2 roles of user interfaces (teacher and student) which link 6 modules and a set of databases and 2 types of contexts (classroom and personal).

Keywords

• Blended Learning,IoT-based technology,Educational technology

References

1. Abowd, G. D. (1999). Classroom 2000: An experiment with the instrumentation of a living educational environment. IBM Systems Journal, 38(4), 508–530. https://doi.org/10.1147/sj.384.0508
2. Abraham, S. (2016). Using Internet of Things (IoT) as a Platform to Enhance Interest in Electrical and Computer Engineering. 2016 ASEE Annual Conference & Exposition Proceedings. https://doi.org/10.18260/p.27149
3. Aftab, H., Gilani, K., Lee, J., Nkenyereye, L., Jeong, S., & Song, J. (2019). Analysis of identifiers on IoT platforms. Digital Communications and Networks. https://doi.org/10.1016/j.dcan.2019.05.003
4. Akyol, Z., & Garrison, R. D. (2008). The Development of a Community of Inquiry Over Time in an Online Course: Understanding the Progression and Integration of Social, Cognitive and Teaching Presence. Journal of Asynchronous Learning Networks, 12(3–4), 3–22.
5. Al-Hitmi, M., & Sherif, K. (2018). Employee perceptions of fairness toward IoT monitoring. VINE Journal of Information and Knowledge Management Systems, 48(4), 504–516. https://doi.org/10.1108/vjikms-01-2018-0007
6. Al-Sharhan, S. (2016). Smart classrooms in the context of technology-enhanced learning (TEL) environment. In M. Ally & K. Alshahrani (Eds.), Transforming Education in the Gulf Region: Emerging Learning Technologies and Innovative Pedagogy for the 21st Century (Routledge Research in Education) (1st ed., pp. 188–214). London, United Kingdom: Routledge.
7. Altamimi, A. B., & Ramadan, R. A. (2016). Towards internet of things modeling: a gateway approach. Complex Adaptive Systems Modeling, 4(1). https://doi.org/10.1186/s40294-016-0038-3
8. Anastasiades, P. S. (2012). Design of a Blended Learning Environment for the Training of Greek Teachers: Results of the Survey on Educational Needs. In P. S. Anastasiades (Ed.), Blended Learning Environments for Adults: Evaluations and Frameworks (1st ed., pp. 230–256). Hershey, Pennsylvania: IGI Global.

9. Atzori, L., Iera, A., & Morabito, G. (2017). Understanding the Internet of Things: definition, potentials, and societal role of a fast evolving paradigm. Ad Hoc Networks, 56, 122–140. https://doi.org/10.1016/j.adhoc.2016.12.004
10. Bonk, C. J., & Graham, C. R. (2007). The Handbook of Blended Learning: Global Perspectives, Local Designs (1st ed.). San Francisco: Pfeiffer.
11. Brumitt, B., Meyers, B., Krumm, J., Kern, A., & Shafer, S. (2000). EasyLiving: Technologies for Intelligent Environments. Handheld and Ubiquitous Computing, 12–29. https://doi.org/10.1007/3-540-39959-3_2
12. Brusilovsky, P., & Peylo, C. (2003). Adaptive and Intelligent Web-based Educational Systems. International Journal of Artificial Intelligence in Education, 13(2–4), 156–172.
13. Casola, V., De Benedictis, A., Rak, M., & Villano, U. (2019). Toward the automation of threat modeling and risk assessment in IoT systems. Internet of Things, 7, 100056. https://doi.org/10.1016/j.iot.2019.100056
14. Celesti, A., Lay-Ekuakille, A., Wan, J., Fazio, M., Celesti, F., Romano, A., Villari, M. (2019). Information management in IoT cloud-based tele-rehabilitation as a service for smart cities: Comparison of NoSQL approaches. Measurement, 151, 107218. https://doi.org/10.1016/j.measurement.2019.107218
15. Chen, W., & Looi , C.-K. (2007). Incorporating online discussion in face to face classroom learning: A new blended learning approach. Retrieved December 30, 2019, from https://www.learntechlib.org/p/44503/.
16. Chiu, C.-K., Tseng, J. C. R., & Hsu, T.-Y. (2016). Blended context-aware ubiquitous learning in museums: environment, navigation support and system development. Personal and Ubiquitous Computing, 21(2), 355–369. https://doi.org/10.1007/s00779-016-0986-9
17. Cockrum, T. (2017). Emerging Models of Practice in Flipped English Language Arts Classrooms. Applying the Flipped Classroom Model to English Language Arts Education, 160–176. https://doi.org/10.4018/978-1-5225-2242-3.ch009
18. Dong, X., Chang, Y., Wang, Y., & Yan, J. (2017). Understanding usage of Internet of Things (IOT) systems in China. Information Technology & People, 30(1), 117–138. https://doi.org/10.1108/itp-11-2015-0272
19. Dorri, A., Kanhere, S. S., & Jurdak, R. (2016). Blockchain in internet of things: Challenges and Solutions. Computing Research Repository, abs/1608.05187. Retrieved from https://arxiv.org/abs/1608.05187
20. Driscoll, M. (2002). Blended learning: let’s get beyond the hype. Retrieved December 30, 2019, from https://www-07.ibm.com/services/pdf/blended_learning.pdf
21. Driscoll, M. (1999). Web-Based Training in the Workplace. Adult Learning, 10(4), 21–25. https://doi.org/10.1177/104515959901000408
22. Driscoll, M. (2010). Web-Based Training: Creating e-Learning Experiences. Hoboken, NJ: Wiley.
23. Dziuban, C., Graham, C. R., Moskal, P. D., Norberg, A., & Sicilia, N. (2018). Blended learning: the new normal and emerging technologies. International Journal of Educational Technology in Higher Education, 15(1). https://doi.org/10.1186/s41239-017-0087-5
24. Fernandez-Carames, T. M., & Fraga-Lamas, P. (2018). A Review on the Use of Blockchain for the Internet of Things. IEEE Access, 6, 32979–33001. https://doi.org/10.1109/access.2018.2842685
25. Garrison, D.R., & Vaughan, N. D. (2011). Blended Learning in Higher Education: Framework, Principles, and Guidelines. Hoboken, NJ: Wiley.
26. Garrison, D.R., Anderson, T., & Archer, W. (1999). Critical Inquiry in a Text-Based Environment: Computer Conferencing in Higher Education. The Internet and Higher Education, 2(2–3), 87–105. https://doi.org/10.1016/s1096-7516(00)00016-6
27. Graham, C. R. (2006). Blended Learning system: definition, current trends and future directions. In C. J. Bonk & C. R. Graham (Eds.), The Handbook of Blended Learning: Global Perspectives, Local Designs (1st ed., pp. 1–21). San Francisco, USA: Wiley, John & Sons, Incorporated.
28. Gubbi, J., Buyya, R., Marusic, S., & Palaniswami, M. (2013). Internet of Things (IoT): A vision, architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645–1660. https://doi.org/10.1016/j.future.2013.01.010
29. Hara, H., & Kuwabara, H. (2015). Innovation in On-site Work Using Smart Devices and Augmented Reality Technology. Fujitzu Science Technology Journal, 51(2), 12–19.
30. Haverinen-Shaughnessy, U., Shaughnessy, R. J., Cole, E. C., Toyinbo, O., & Moschandreas, D. J. (2015). An assessment of indoor environmental quality in schools and its association with health and performance. Building and Environment, 93, 35–40. https://doi.org/10.1016/j.buildenv.2015.03.006
31. Hwang, G.-J. (2014). Definition, framework and research issues of smart learning environments - a context-aware ubiquitous learning perspective. Smart Learning Environments, 1(1). https://doi.org/10.1186/s40561-014-0004-5
32. Hwang, G.-J., Tsai, C.-C., & Yang , S. J. H. (2008). Criteria, strategies and research issues of context-aware ubiquitous learning. Education Technology Society, 11(2), 81–91.
33. International Telecommunication Union-Telecommunication standardization sector. (2012). Overview of the internet of things, Recommendation ITU-T Y.2060. Retrieved November 10, 2019, from http://handle.itu.int/11.1002/1000/11559
34. Jeon, Y., Cho, C., Seo, J., Kwon, K., Park, H., Oh, S., & Chung, I.-J. (2018). IoT-based occupancy detection system in indoor residential environments. Building and Environment, 132, 181–204. https://doi.org/10.1016/j.buildenv.2018.01.043
35. Jin, M., Bekiaris-Liberis, N., Weekly, K., Spanos, C. J., & Bayen, A. M. (2018). Occupancy Detection via Environmental Sensing. IEEE Transactions on Automation Science and Engineering, 15(2), 443–455. https://doi.org/10.1109/tase.2016.2619720
36. Johanson, B., Fox, A., & Winograd, T. (2002). The Interactive Workspaces project: experiences with ubiquitous computing rooms. IEEE Pervasive Computing, 1(2), 67–74. https://doi.org/10.1109/mprv.2002.1012339
37. Koper, R. (2014). Conditions for effective smart learning environments. Smart Learning Environments, 1(1), 1–17. https://doi.org/10.1186/s40561-014-0005-4
38. Koucheryavy, A., Makolkina, M., & Paramonov, A. (2016). Applications of Augmented Reality Traffic and Quality Requirements Study and Modeling. Communications in Computer and Information Science, 241–252. https://doi.org/10.1007/978-3-319-51917-3_22
39. Lewis, L., & Parsad, B. (2008). Distance education at degree-granting postsecondary institutions : 2006–07 (NCES 2009–044). Retrieved from https://nces.ed.gov/pubs2009/2009044.pdf
40. Li, S., Xu, L. D., & Zhao, S. (2015). The internet of things: a survey. Information Systems Frontiers, 17(2), 243–259. https://doi.org/10.1007/s10796-014-9492-7
41. Liang, X., & Chen, Y. (2018). Libraries in Internet of Things (IoT) era. Library Hi Tech. https://doi.org/10.1108/lht-11-2017-0233
42. Makolkina, M., Koucheryavy, A., & Paramonov, A. (2017). The Models of Moving Users and IoT Devices Density Investigation for Augmented Reality Applications. Lecture Notes in Computer Science, 671–682. https://doi.org/10.1007/978-3-319-67380-6_64
43. McNall, L. A., & Stanton, J. M. (2010). Private Eyes Are Watching You: Reactions to Location Sensing Technologies. Journal of Business and Psychology, 26(3), 299–309. https://doi.org/10.1007/s10869-010-9189-y
44. Minoli, D., & Occhiogrosso, B. (2018). Blockchain mechanisms for IoT security. Internet of Things, 1–2, 1–13. https://doi.org/10.1016/j.iot.2018.05.002
45. Miorandi, D., Sicari, S., De Pellegrini, F., & Chlamtac, I. (2012). Internet of things: Vision, applications and research challenges. Ad Hoc Networks, 10(7), 1497–1516. https://doi.org/10.1016/j.adhoc.2012.02.016
46. Moskal, P., Dziuban, C., & Hartman, J. (2013). Blended learning: A dangerous idea? The Internet and Higher Education, 18(2013), 15–23.
47. Norberg , A., & Jahnke, I. (2013). Are You Working in the Kitchen? – European Perspectives on Blended Learning. In A. G. Picciano, C. D. Dziuban, & C. R. Graham (Eds.), Blended Learning: Research Perspectives (pp. 251–267). Oxfordshire, United Kingdom: Taylor & Francis.
48. Norberg, A. (2017). From blended learning to learning onlife - ICTs, time and access to higher education. Umeå University Umeå: Sweden: Department of Applied Educational Science, Print and Media.
49. Norberg, A., Dziuban, C. D., & Moskal, P. D. (2011). A time‐based blended learning model. On the Horizon, 19(3), 207–216. https://doi.org/10.1108/10748121111163913
50. Norberg, A., Händel, Å., & Ödling, P. (2015). Using MOOCs at Learning Centers in Northern Sweden. The International Review of Research in Open and Distributed Learning, 16(6). https://doi.org/10.19173/irrodl.v16i6.2035
51. Norberg, A., Stöckel, B., & Antti, M.-L. (2017). Time Shifting and Agile Time Boxes in Course Design. The International Review of Research in Open and Distributed Learning, 18(6). https://doi.org/10.19173/irrodl.v18i6.3182
52. Pan, J., Wang , J., Hester, A., AlQerm, I., Liu, Y., & Zhao, Y. (2018). EdgeChain: An Edge-IoT Framework and Prototype Based on Blockchain and Smart Contracts. Computing Research Repository, abs/1806.06185. Retrieved from https://arxiv.org/abs/1806.06185
53. Perera, C., Zaslavsky, A., Christen, P., & Georgakopoulos, D. (2014). Context Aware Computing for The Internet of Things: A Survey. IEEE Communications Surveys & Tutorials, 16(1), 414–454. https://doi.org/10.1109/surv.2013.042313.00197
54. Probst, A., Schachinger, G., Kalteis, G., & Fischer, A. (2019). New Technologies as a Driver for Business Success. International Journal of Engineering Pedagogy (IJEP), 9(1), 102. https://doi.org/10.3991/ijep.v9i1.9866
55. Ratto, M., Shapiro, R. Benjamin , Truong, T. M., & Griswold, W. G. (2013). The ActiveClass project: Experiments in encouraging classroom participation. In B. Wasson, S. Ludvigsen, & U. Hoppe (Eds.), Designing for Change in Networked Learning Environments (pp. 477–486). New York City, NY: Springer Publishing.
56. Savjani , R. (2019). 5 Factors to Consider Before Choosing an IoT Platform Vendor. Retrieved December 30, 2019, from https://www.softwebsolutions.com/resources/IoT-platform-company.html
57. Shi, Y., Xie, W., Xu, G., & Shi, R. (2003). The smart classroom: merging technologies for seamless tele-education. IEEE Pervasive Computing, 2(2), 47–55. https://doi.org/10.1109/mprv.2003.1203753
58. Shih, T. K., Chang, W.-C., Wang, T.-H., Lin, H. W., Chang, H.-P., Huang, K.-H., Yang, J.-T. (2005). The hard SCORM LMS: reading SCORM courseware on hardcopy textbooks. Fifth IEEE International Conference on Advanced Learning Technologies (ICALT’05). https://doi.org/10.1109/icalt.2005.272
59. Siddiqui, F., Beley, J., Zeadally, S., & Braught, G. (2019). Secure and lightweight communication in heterogeneous IoT environments. Internet of Things, 100093. https://doi.org/10.1016/j.iot.2019.100093
60. Sivathanu, B. (2018). Adoption of internet of things (IOT) based wearables for healthcare of older adults – a behavioural reasoning theory (BRT) approach. Journal of Enabling Technologies, 12(4), 169–185. https://doi.org/10.1108/jet-12-2017-0048
61. Suo, Y., Miyata, N., Morikawa, H., Ishida, T., & Shi, Y. (2009). Open Smart Classroom: Extensible and Scalable Learning System in Smart Space Using Web Service Technology. IEEE Transactions on Knowledge and Data Engineering, 21(6), 814–828. https://doi.org/10.1109/tkde.2008.117
62. Suo, Y., & Shi, Y. (2008). Towards Blended Learning Environment Based on Pervasive Computing Technologies. Hybrid Learning and Education, 190–201. https://doi.org/10.1007/978-3-540-85170-7_17
63. Terroso-Saenz, F., González-Vidal, A., Ramallo-González, A. P., & Skarmeta, A. F. (2019). An open IoT platform for the management and analysis of energy data. Future Generation Computer Systems, 92, 1066–1079. https://doi.org/10.1016/j.future.2017.08.046
64. Thai, N. T. T., De Wever, B., & Valcke, M. (2017). The impact of a flipped classroom design on learning performance in higher education: Looking for the best “blend” of lectures and guiding questions with feedback. Computers & Education, 107, 113–126. https://doi.org/10.1016/j.compedu.2017.01.003
65. Tsunoda, H., & Mansfield Keeni, G. (2016). Societal Model for Securing Internet of Things | TNI Journal of Business Administration and Languages. Retrieved December 30, 2019, from https://www.tci-thaijo.org/index.php/TNIJournalBA/article/view/151631
66. Utts, J., Sommer, B., Acredolo, C., Maher, M. W., & Matthews, H. R. (2003). A Study Comparing Traditional and Hybrid Internet-Based Instruction in Introductory Statistics Classes. Journal of Statistics Education, 11(3). https://doi.org/10.1080/10691898.2003.11910722
67. Uzelac, A., Gligoric, N., & Krco, S. (2015). A comprehensive study of parameters in physical environment that impact students’ focus during lecture using Internet of Things. Computers in Human Behavior, 53, 427–434. https://doi.org/10.1016/j.chb.2015.07.023
68. Wang, Q., Zhu, X., Ni, Y., Gu, L., & Zhu, H. (2019). Blockchain for the IoT and industrial IoT: A review. Internet of Things, 100081. https://doi.org/10.1016/j.iot.2019.100081
69. Xie, W., Shi, Y., Xu, G., & Xie, D. (2001). Smart Classroom - an Intelligent Environment for Tele-education. Advances in Multimedia Information Processing — PCM 2001, 662–668. https://doi.org/10.1007/3-540-45453-5_85